Chenhao Li
About Chenhao Li
Chenhao Li is a Research Fellow currently at Massachusetts General Hospital and the Broad Institute of MIT and Harvard, focusing on multi-omics data analysis in metagenomics and spatial transcriptomics. He holds a Ph.D. in Computational Biology and has extensive experience in bioinformatics, having previously worked at the Genome Institute of Singapore.
Current Role at Broad Institute
Chenhao Li currently holds the position of Research Fellow at the Broad Institute of MIT and Harvard. He has been in this role since 2020, contributing to various research initiatives. His work primarily involves the integrative analysis of multi-omics data, focusing on applications in metagenomics. This position allows him to collaborate with leading researchers in the field and engage in cutting-edge scientific projects.
Previous Experience at Genome Institute of Singapore
Prior to his current role, Chenhao Li worked at the Genome Institute of Singapore in several capacities. He served as a Bioinformatics Specialist from 2014 to 2019, where he developed methods for spatial transcriptomics data analysis. Following this, he was a Postdoctoral Fellow for one year, from 2019 to 2020, focusing on advanced bioinformatics research. He also held the position of Research Associate for a brief period in 2020.
Educational Background in Computational Biology
Chenhao Li completed his Bachelor of Science (B.Sc.) in Computational Biology at the National University of Singapore from 2010 to 2014. He furthered his education by obtaining a Doctor of Philosophy (Ph.D.) in Computer Science with a focus on Computational Biology from the same institution, studying from 2015 to 2019. This educational foundation has equipped him with the skills necessary for his research in bioinformatics and data analysis.
Research Focus and Expertise
Chenhao Li specializes in the integrative analysis of multi-omics data, particularly in the field of metagenomics. His research includes conducting single-cell RNA-Seq analysis of tissue data, which is essential for understanding cellular functions and interactions. His expertise in developing methods for spatial transcriptomics data analysis further enhances his contributions to the field.